Difference between revisions of "Toward a gold standard for benchmarking gene set enrichment analysis"
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Revision as of 15:41, 25 February 2020
__ NUMBEREDHEADINGS__
Contents
Citation
Geistlinger, L., Csaba, G., Santarelli, M., Ramos, M., Schiffer, L., Law, C., ... & Zimmer, R., Toward a gold standard for benchmarking gene set enrichment analysis, 2020, Bioinformatics, 0, 1-12
Summary
Briefly describe the scope of the paper, i.e. the field of research and/or application.
Study outcomes
List the paper results concerning method comparison and benchmarking:
Outcome O1
The performance of ...
Outcome O1 is presented as Figure X in the original publication.
Outcome O2
...
Outcome O2 is presented as Figure X in the original publication.
Outcome On
...
Outcome On is presented as Figure X in the original publication.
Further outcomes
If intended, you can add further outcomes here.
Study design and evidence level
General aspects
- "75 expression datasets investigating 42 human diseases"
- microarray and RNAseq data
- pre-existing benchmark data sets
- 10 methods:
- ORA
- GLOBALTEST
- GSEA
- SAFE
- GSA
- SAMGS
- ROAST
- CAMERA
- PADOG
- GSVA
- "Gene set relevance rankings for each disease were constructed by querying the MalaCards database. MalaCards scores genes for disease relevance based on experimental evidence and co-citation in the literature."
Design for Outcome O1
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
Design for Outcome O2
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
...
Design for Outcome O
- The outcome was generated for ...
- Configuration parameters were chosen ...
- ...
Further comments and aspects
References
The list of cited or related literature is placed here.